Update app.py

app.py

@@ -5,7 +5,7 @@ import gradio as gr
 from transformers import AutoTokenizer
 from huggingface_hub import hf_hub_download
 
-# Hide background warning logs
+# Silence background warning logs
 os.environ["TRANSFORMERS_NO_ADVISORY_WARNINGS"] = "1"
 
 REPO_ID = "Havoc999/distilbert-imdb-sentiment-onnx"
@@ -41,17 +41,12 @@ def predict_sentiment(text):
     exp_logits = np.exp(logits - np.max(logits))
     scores_array = exp_logits / np.sum(exp_logits)
     
-    # 4. Force into a plain Python list (destroys NumPy types instantly)
+    # 4. Convert NumPy array directly to standard Python floats inside a list
     clean_scores = scores_array.tolist()
     
-    # 5. Extract items out one by one into independent variables
-    negative_final_score = float(clean_scores)
-    positive_final_score = float(clean_scores)
-    
-    return {
-        "Negative 🎬❌": negative_final_score,
-        "Positive 🍿✅": positive_final_score
-    }
+    # 5. NO INDEXES OR FLICKERING TYPOS: Map labels directly to values
+    labels = ["Negative 🎬❌", "Positive 🍿✅"]
+    return dict(zip(labels, clean_scores))
 
 # 6. Set up the web interface
 demo = gr.Interface(